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This paper introduces a topological localization algorithm that uses visual and Wi-Fi data. Its main contribution is a novel way of merging data from these sensors. By making Wi-Fi signature suited to FABMAP algorithm, it develops an early-fusion framework that solves global localization and kidnapped robot problem. The resulting algorithm is tested and compared to FABMAP visual localization, over...
With the fast development of Geographic Information Systems, visual global localization has gained a lot of attention due to the low price of a camera and the practical implications. In this paper, we leverage Google Street View and a monocular camera to develop a refined and continuous positioning in urban environments: namely a topological visual place recognition and then a 6 DoF pose estimation...
This paper presents a metric global localization in the urban environment only with a monocular camera and the Google Street View database. We fully leverage the abundant sources from the Street View and benefits from its topo-metric structure to build a coarse-to-fine positioning, namely a topological place recognition process and then a metric pose estimation by local bundle adjustment. Our method...
This paper presents a novel approach to self calibrate the extrinsic parameters of a camera mounted on a mobile robot in the context of fusion with the odometry sensor. Calibrating precisely such a system can be difficult if the camera is mounted on a vehicle where the frame is difficult to localize precisely (like on a car for example). However, the knowledge of the camera pose in the robot frame...
This paper presents a novel approach to self calibrate the extrinsic parameters of a camera mounted on a mobile robot in the context of fusion with the odometry sensor. Calibrating precisely such a system can be difficult if the camera is mounted on a vehicle where the frame is difficult to localize precisely (like on a car for example). However, the knowledge of the camera pose in the robot frame...
Autonomous and safe robot navigation requires the capability to simultaneously building a map of the environment and a selflocalization of the robot itself. This is known as the SLAM (Simultaneous Localization and Mapping) problem. In such a context, omnidirectional camera looks like a very interesting sensor since it allows a full 360 degrees field of vision. Complexity of the SLAM methods dramatically...
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